Computers are increasingly featuring direct touch interfaces, found in forms as diverse as kiosks and interactive tabletops, to tablet computers and handheld mobile devices. At present, finger input on touch screens is handled very simplistically, often boiled down to an X/Y coordinate. Many technologies exist that have the ability to digitize different types of input. There are two main touch sensing approaches: active and passive. The key downside of active approaches is that an explicit object must be used (e.g., a special pen), which is implemented with electronics (and batteries if not tethered). For example, pens augmented with infrared light emitters on their tips can be used on the commercially available Microsoft Surface. There have also been efforts to move beyond pens, including, e.g., infrared-light-emitting brushes for painting applications. Current systems generally do not attempt to discriminate among different pens (just perhaps pen from finger input). Variably-modulated infrared light enables identification, but requires specialized hardware. Additionally, ultrasonics can be used for input localization, and can provide pen ID as well. Capacitive coupling in allows users or objects to be localized and identified, though this requires grounding plates or a physical connection to function.
Sensing based on electromagnetic resonance, another method, operates between active and passive. Although the tools and tangibles need not be powered, they contain a resonant coil that is excited by proximate EM fields, generated by the specialized tablet they operate on. Although highly capable, including the ability to provide ID, table-sized setups are prohibitively expensive at present. It is also possible to support object identification through a combination of RFID and vision processing, which offers greater scalability.
Fiducial markers are a truly passive approach. They provide the ID of an object through a uniquely patterned tag—often in a sticker form factor. This method has been shown to be very capable—the only major drawback is the size of the marker, which in general, prevents placement on small surfaces like the tip of a pen. Fiducial markers can also work in a capacitive-sensing manner, allowing tags to be embedded in an object. Additionally, the shape of an object can be captured optically and used for classification (e.g., mice and keyboards).
In general, the aforementioned techniques require instrumentation of the object providing input, which is problematic for fingers (i.e., people do not like to wear things on their fingers and hands). Researchers have also looked at wrist-mounted acoustic sensors that can classify finger-on-finger actions, such as pinching or flicking. Finger taps can also be localized on the body through acoustic fingerprinting. However, the latter systems require sensors to be placed on the user.
Without instrumentation, some areas of the finger can be determined through computer vision (e.g., pad vs. tip). Using accelerometers, soft and hard taps can be discriminated. Finally, time of flight analysis can be used to localize touch events on the surface of an object.
Contemporary interactive surfaces generally treat finger touches as a single class of input (a partial exception to this are finger-print scanning systems, which can capture a high-resolution fingerprint image to infer the 3D “posture” of a finger; also, area of contact via optical or capacitive sensing can be considered an extra input dimension). However, this is a gross simplification—fingers are diverse appendages, both in their motor capabilities and their anatomical composition. Supporting additional dimensions of finger input has largely been ignored because instrumenting the user with active or passive components is invasive.